In an increasingly competitive marketplace that demands more value faster, the word \u201cautomation\u201d has become synonymous with \u201cefficiency.\u201d Organizations are scrambling to automate business processes with the hopes of quickly streamlining operations and gaining a competitive edge.<\/p>\n
After all, when automation works well, it\u2019s a masterpiece of coordination and execution. It removes human error as it swiftly automates processes straight to production. Profits soar, investors are happy, and everybody wins.<\/p>\n
In reality, automation brings speed to processes \u2013 and speed is often mistaken for efficiency. When we automate processes that aren\u2019t ready for automation, we can accelerate and intensify their flaws to produce faster, more spectacular failures. <\/strong><\/p>\n Let\u2019s consider luxury automaker Tesla\u2019s recent automation blunder. CEO Elon Musk announced his plan to fully automate Tesla\u2019s factory assembly line in 2018. By the end of the first quarter, he was forced to admit that excessive automation had actually slowed down production. The over-reliance on robots on the assembly line had created enough chokepoints in the manufacturing process that Tesla missed production goals and the company\u2019s stock took a first quarter nose dive.<\/p>\n Mr. Musk learned the hard way that automating isn\u2019t the same thing as becoming more efficient. In fact, it can have the exact opposite effect.<\/strong><\/p>\n Tesla\u2019s assembly line breakdown resulted from over-automating <\/strong>a complex process that required human interaction at critical junctures, as well as tactile precision with some of the finer assembly tasks such as placing fiberglass on top of batteries. Rather than improving efficiency on the line, robots had slowed it down because they were unable to self-correct when unforeseen issues arose. As Musk himself remarked, \u201cHumans are underrated.\u201d<\/p>\n Grafting is another practice which can cause the best laid plans to go awry. When we simply overlay existing technology and processes with new technology, it can create serious problems. General Motors\u2019 (GM) infamous automation experiment provides a classic example.<\/strong><\/p>\n In the 1980s, GM went out on a limb to compete with Toyota, which was quickly eroding GM\u2019s market share. They invested in spray painting robots to save time and personnel hours on the paint line. Unfortunately, the robots and vehicles fell out of sync when the computer-guided dolly veered slightly off course.<\/p>\n The robots began to misfire, mostly spray painting each other. This colorful fiasco resulted in an expensive production delay since the affected vehicles had to be sanded down and repainted at another facility.<\/p>\n Before investing in automation, it is imperative for organizations to evaluate their internal processes to determine IT delivery process readiness.<\/strong> We need to know which processes are ready for automation, which require re-engineering before automation should be considered, and which processes should remain manual indefinitely.<\/p>\n There are three main factors to consider when assessing IT delivery process readiness:<\/strong><\/p>\n While automation alone will not improve a business process, it can and should evolve with<\/u><\/em> the processes in the DevOps space. Organizations first need to understand the current state of their business processes before making major investments in automation.<\/p>\nAssessing IT Delivery Process Readiness<\/h2>\n
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Sound Principles for Process Change Through Automation:<\/h2>\n
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Final Thoughts<\/h2>\n